Order Picking Problem in a Warehouse with Bi-Objective Genetic Algorithm Approach: Case Study | Zendy

Şafak Kırış | Zendy; Derya Deli̇ktaş | Zendy; Özden ÜSTÜN | Zendy

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Order Picking Problem in a Warehouse with Bi-Objective Genetic Algorithm Approach: Case Study

Author(s) -

Şafak Kırış,

Derya Deli̇ktaş,

Özden ÜSTÜN

Publication year - 2018

Publication title -

doğuş üniversitesi dergisi

Language(s) - English

Resource type - Journals

eISSN - 1308-6979

pISSN - 1302-6739

DOI - 10.31671/dogus.2018.15

Subject(s) - warehouse , genetic algorithm , order (exchange) , computer science , order picking , algorithm , mathematical optimization , mathematics , machine learning , business , finance , marketing

In this paper, an order picking problem with the capacitated forklift in a warehouse is studied by considering the total distance and the penalized earliness/tardiness. These objectives are important to reduce transportation costs and to satisfy customer expectations. Since this problem has been known as NP-hard, a genetic algorithm (GA) is proposed to solve the bi-objective order picking problem. The proposed approach is applied to auto components industry that produces wire harnesses responsible for all electrical functions in the vehicle. Experimental design is used for tuning the influential parameters of the proposed GA. The GA approach was solved by weighted sum scalarization.

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